Initial commit: Project foundation and architecture

- Add project requirements document
- Add comprehensive architecture design
- Add README with quick start guide
- Add .gitignore for Python/Docker/Node

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

PROJECT_REQUIREMENTS.md

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+# T6 Mem0 v2 - Project Requirements
+
+## Original User Request
+
+**Date**: 2025-10-13
+
+### Core Objectives
+
+Set up a comprehensive memory system with the following capabilities:
+- **MCP Server Integration**: Serve as an MCP server for Claude and other LLM-based systems
+- **REST API Access**: Enable memory storage and retrieval via REST API
+- **Data Storage**: Use locally running Supabase for primary data storage
+- **Graph Visualization**: Use Neo4j for storing and visualizing memory relationships
+- **LLM Integration**: Initial phase with OpenAI, future phase with local Ollama instance
+
+### Technology Stack
+
+**Phase 1 (Initial Implementation)**:
+- mem0.ai as the core memory framework
+- Supabase (local instance) for vector and structured storage
+- Neo4j for graph-based memory relationships
+- OpenAI API for embeddings and LLM capabilities
+- MCP (Model Context Protocol) server for AI agent integration
+
+**Phase 2 (Future)**:
+- Local Ollama integration for LLM independence
+- Additional local model support
+
+### Key Requirements
+
+1. **MCP Server**: Must function as an MCP server that can be used by Claude Code and other LLM systems
+2. **REST API**: Full REST API for CRUD operations on memories
+3. **Local Infrastructure**: All data storage must be local (Supabase, Neo4j)
+4. **Visualization**: Neo4j integration for memory graph visualization
+5. **Documentation**: Mintlify-based documentation site
+6. **Version Control**: Git repository at https://git.colsys.tech/klas/t6_mem0_v2
+
+### Repository Information
+
+- **Git Remote**: https://git.colsys.tech/klas/t6_mem0_v2
+- **Username**: klas
+- **Password**: csjXgew3In
+
+### Project Phases
+
+#### Phase 1: Foundation
+- Research and validate mem0.ai capabilities
+- Design architecture with Supabase + Neo4j + OpenAI
+- Implement core memory storage and retrieval
+- Build MCP server interface
+- Create REST API endpoints
+- Set up Mintlify documentation
+
+#### Phase 2: Local LLM Integration
+- Integrate Ollama for local model support
+- Add model switching capabilities
+- Performance optimization for local models
+
+### Success Criteria
+
+- Functional MCP server that Claude Code can use
+- Working REST API for memory operations
+- Memories persisted in local Supabase
+- Graph relationships visible in Neo4j
+- Complete documentation in Mintlify
+- All code versioned in git repository